manucastle
02-14-2012, 04:17 AM
Over the week-end and last week, I have applied the GDX model to a few industry groups: XLE, XLI, XLK, XLU and SPY.
The results are below:
12795
First, let me say that this is "on-going work". There is still further analysis work to be made in regards to:
- Draw downs
- Trade statistics
- Correlation
- Stock selection within each industry group
- Complete these tables with XLB, XLY, XLP, XLV
What I did was simply to use the OB/OS GDX MF model and apply it "as is" to the different industry group.
The OB/OS and the porosity levels are automatically adapted (using only past but more recent data than very old past data).
Let me already comment on the first results:
1. In blue, I highlighted the positive returns for 2008 on the 20DMF, SPY and GDX models groups, while the four other groups were negative. There is one reason for this: data! For the four XL groups, I indeed took the group's composition/weight as of today and applied it down to 2008. However, in 2008/2009, there were 63 changes in the S&P500, 16 in 2010 and 12 in 2011. With the weights also changing, this means that the older the data, the less reliable the results will be. For the S&P500, I manually kept track of all the past changes (I did not do that for the underlying groups.) I also think that for GDX, the index has been very stable since many years with the larger stocks taking the "bulk" of the index: ABX, GG, KGC, SLW, etc...
2. Because of this and also because 2008/2009 were really exceptional trending years, I prefer to concentrate on the results for the past two years, shown in yellow and green. The yellow represents the total of the past two years, while the green color highlights the difference between the model and the corresponding ETF return.
We can see that:
2.A. The model works well for XLK, XLI, XLE and less so for SPY and XLU. I understand that it would not work well for SPY, which involves all the sectors, while each sub-group is more focused and hence, the movements of money are easier to detect when we analyse each group separately. This however does not explain the fact that the model does not act so well with XLU. It might be a lack of volatility in this sub-group, but I had no time to study trades in detail to point this out.
2.B. We should also note that XLU ETF acted well in 2011, while all other sectors were poor. We indeed had a defensive market in 2011. However, the model could take advantage of the groups' inherent volatility.
2.C. GDX offered the strongest returns. This is also due to the higher volatility and waves of changes that is a characteristic of this sector.
3.For the past two years, the XLE model did better than the 20DMF and the XLI model did almost as good as the 20DMF. This means that there is something to dig around here with probably the possibility to rotate between industry groups independently from the 20DMF itself.
Pascal
Pascal, in the EV database under 'ETF Review' you have graphs for all the sectors apart from XLI.
Am I missing something or, if not, can you add it please ?
Trev
The results are below:
12795
First, let me say that this is "on-going work". There is still further analysis work to be made in regards to:
- Draw downs
- Trade statistics
- Correlation
- Stock selection within each industry group
- Complete these tables with XLB, XLY, XLP, XLV
What I did was simply to use the OB/OS GDX MF model and apply it "as is" to the different industry group.
The OB/OS and the porosity levels are automatically adapted (using only past but more recent data than very old past data).
Let me already comment on the first results:
1. In blue, I highlighted the positive returns for 2008 on the 20DMF, SPY and GDX models groups, while the four other groups were negative. There is one reason for this: data! For the four XL groups, I indeed took the group's composition/weight as of today and applied it down to 2008. However, in 2008/2009, there were 63 changes in the S&P500, 16 in 2010 and 12 in 2011. With the weights also changing, this means that the older the data, the less reliable the results will be. For the S&P500, I manually kept track of all the past changes (I did not do that for the underlying groups.) I also think that for GDX, the index has been very stable since many years with the larger stocks taking the "bulk" of the index: ABX, GG, KGC, SLW, etc...
2. Because of this and also because 2008/2009 were really exceptional trending years, I prefer to concentrate on the results for the past two years, shown in yellow and green. The yellow represents the total of the past two years, while the green color highlights the difference between the model and the corresponding ETF return.
We can see that:
2.A. The model works well for XLK, XLI, XLE and less so for SPY and XLU. I understand that it would not work well for SPY, which involves all the sectors, while each sub-group is more focused and hence, the movements of money are easier to detect when we analyse each group separately. This however does not explain the fact that the model does not act so well with XLU. It might be a lack of volatility in this sub-group, but I had no time to study trades in detail to point this out.
2.B. We should also note that XLU ETF acted well in 2011, while all other sectors were poor. We indeed had a defensive market in 2011. However, the model could take advantage of the groups' inherent volatility.
2.C. GDX offered the strongest returns. This is also due to the higher volatility and waves of changes that is a characteristic of this sector.
3.For the past two years, the XLE model did better than the 20DMF and the XLI model did almost as good as the 20DMF. This means that there is something to dig around here with probably the possibility to rotate between industry groups independently from the 20DMF itself.
Pascal
Pascal, in the EV database under 'ETF Review' you have graphs for all the sectors apart from XLI.
Am I missing something or, if not, can you add it please ?
Trev